Abstract: Does the economic effect of immigrant women differ from that of immigrants in general? This paper examines if gender has influenced the short- and long-term economic impact of mass migration to the US, using Census microdata from 1880 and 1910. By means of ordinary least squares and instrumental variable estimations, the analysis shows that a greater concentration of immigrant women is significantly associated with lower levels of economic development in US counties. However, immigrant women also shaped economic development positively, albeit indirectly via their children. Communities with more children born to foreign mothers and that successfully managed to integrate female immigrants experienced greater economic growth than those dominated by children of foreign-born fathers or American-born parents.

What is the economic impact of female migration? The authors seek to answer the inquiry by using the United States in the late 19th and early 20th century as their study case. The goal of the paper is to highlight the distinctiveness of women immigration (compared to that of men), both in the processes that led women to migrate, the characteristics they had, and the places where they finally settled. The main thesis of paper stresses the long-lasting effect women have had; through their family role, as mothers, they facilitated the formation and transmission of social capital, which had a pervasive positive effect on income.

Female migrants in early America tended to settle mainly on urbanized areas in the Northeastern coast – compared to that of male immigrants (who settled mainly in the South and West). The migration levels of women, in absolute terms, were lower, and their marriage rates higher. More importantly, their labor participation rates were low: women tended to stay and work in domestic chores rather than find occupations in the market. These characteristics make female migration distinct to that of men, and motivate the goal of the paper in trying to assess their particular relevance.

Figure 1: Immigrant Women in the United States, 1880. By the nature of the variable, counties with a larger share of immigrant women imply a lower share of immigrant men.

The text relies on standard econometric analyses, based on intuition and on the literature of migration and culture transmission. The main data sources are the historical censuses of 1880 and 1910, which capture the amount of, male and female foreign-born population residents in each US county (among other data). The paper presents two base regressions that aim to assess the direct and indirect economic impact of female migration, both in the short and the long term. The first model regresses economic income (GDP per capita by county) on female migration (foreign-born women as a share of the total population in the county). They find that the variables are negatively correlated: lack of labor market participation hindered the female contribution to income. The authors also found that this has had a long term negative effect (income today is also negatively correlated with female migration in late 19th and early 20th century) [1]. To correct for potential biases and to establish a causality linkage that goes strictly from migration to income, and not the other way around, the authors use three different instruments: a) the percentage of married persons; b) the number of persons living in a household; c) the urbanization rate of the county being examined. The first instrument accounts for the fact that female migrants tended to be married in larger shares than the rest of the population. The second accounts for the idea that migrants, especially women, tended to stay with members of their families through their lifetime. The last one maintains that female migrants favored settlement in urbanized zones. The validity of an instrument (marriage percentage, household size and urbanization) hinges upon it being correlated with the dependent variable (income) only by it causing the highlighted mechanism (female migration). The authors do several post-hoc statistical tests to evaluate the instrument’s validity and conclude that it is indeed a valid and strong one. In any case, the instrument variable outcomes do not change the results of the baseline ordinary least squares scenario, they just allow a more robust interpretation of them: it can be said that female migration did have a negative impact on income.

The second model emphasizes the indirect impact of migrant women. Maybe women themselves did not positively contribute to the economic wellbeing of their communities, but they could have done so through other means. The authors refer to the literature that stresses how mothers influence their children behavior and thus have an important role as social capital transmitters (which could positively affect economic wellbeing). They regress economic income today on the share of children (in 1880 and 1910) born from: 1) a migrant mother and an American-born father; 2) a migrant father and an American mother; 3) both American parents. The standard base of comparison is the share of children that had both parents as immigrants [2]. By definition, the model can only capture the long-term effect of female migrants. The authors find that US counties with an historical larger share of children with migrant mothers are correlated with larger incomes today – in comparison to the other explanatory variables; having American parents is negatively correlated with income today; having a migrant father, and American mother, has a non-significant and null effect on economic outcomes today. The argument, again, rests on the case of social capital transmission: women, as mothers, matter very much. To corroborate their OLS results they also use an instrumental variable. The authors assume that American-born women that had migrant mothers followed the cultural transmission pattern established by their forebears. They call this the “supply-push” component, which they estimate and use as their instrument. Just as the first model, the instrumental variable inclusion does not modify the basic results, it only permits to talk about causality from migrants in the past to better economic outcomes today.

In conclusion, the paper finds that female immigration, while having a negative direct short-term impact on economic income, has a long-lasting positive effect through the “cultural carrier” channel.

Comment

The paper is a very interesting one, being one of the few studies that aims to disentangle the impact of women as migrants compared to that of men. The results the authors present make intuitive sense. I would like to make just small technical comments based on the variables they use and how they use them.

First, related to the semantics of the concept of “migration.” Migration is normally thought as a flow variable, but here it is used as a stock variable. Given the data they use (measuring migrants as people classified as foreign born in two censuses) the authors cannot measure the impact of migration as a flow, only the impact of it in broad terms. This is not a problem. I just would have liked to see a minor explanation on the paper that clarified the interpretations that we could get out of this. In fact, I think it could explain why they find a negative impact of migrant women in income (if the variables were flows, through migration rates and economic growth, the results may be different).

Second, on a more technical note, I’m skeptic of the instruments being used. Even though the authors argue that they are valid and strong, I remain unconvinced. The authors show that all four of them are correlated with the dependent variable and uncorrelated with the error terms, yet there is almost no explanation, backed up by a narrative, of how exactly these instruments impact on income only through female migration. For each one of the instruments used I could think of other alternate channels by which they could impact income. For example, the use of percentage of marriage by county could indeed be correlated with female migration, but is that the only potential channel? Could it not be that maybe poverty or religion could be impacting income as well?

Lastly, I wish the narrative part could be explained in larger detail. For example, how exactly female migrants in 1880 have a direct impact on income in 2010. Or how exactly children of foreign mothers in 1880 and 1910 could affect income today. It is one thing to say that culture matters, it is another different thing to point how exactly it does. In fact, even though they do mention the pervasiveness of cultural traits through time, they fail to mention that this pervasiveness does not imply ipso facto a good outcome is assured. Sometimes, social capital is also correlated with bad outcomes.

[1] The authors do not provide a concise explanation of why this could be happening: how could a century year old female migration pattern directly impact economic wellbeing today?

[2] All the interpretations of results are in comparison to that baseline.

The Rise of American Ingenuity: Innovation and Inventors of the Golden Age
By Ufuk Akcigit (University of Chicago), John Grigsby (University of Chicago) and Tom Nicholas (Harvard Business School)

Abstract: We examine the golden age of U.S. innovation by undertaking a major data collection exercise linking historical U.S. patents to state and county-level aggregates and matching inventors to Federal Censuses between 1880 and 1940. We identify a causal relationship between patented inventions and long-run economic growth and outline a basic framework for analyzing key macro and micro-level determinants. We find a positive relationship between innovation and drivers of regional performance including population density, financial development and geographic connectedness. We also explore the impact of social structure measured by slavery and religion. We then profile the characteristics of inventors and their life cycle finding that inventors were highly educated, positively selected through exit early in their careers, made time allocation decisions such as delayed marriage, and tended to migrate to places that were conducive to innovation. Father’s income was positively correlated with becoming an inventor, though not when controlling for the child’s education. We show there were strong financial returns to technological development. Finally, we document an inverted-U shaped relationship between inequality and innovation but also show that innovative places tended to be more socially mobile. Our new data help to address important questions related to innovation and long-run growth dynamics.

In this paper Akcigit, Grisby, and Nicholas highlight the advancement of transportation technology in the United States between 1880 and 1940, while better transport responded to the need to link the more developed and innovative regions of the country. Akcigit, Grisby and Nicholas find that the American transport links were much stronger and of better quality between more developed regions in terms of finance and innovation, which, in turn, Hart and Milstein (2003) point to as key aspects for a successful capitalist society.

Research by Akcigit, Grisby and Nicholas is in line with others such as Harris (2015), who highlights that there is a direct link between advancements in technology and the growth of globalisation. The findings by Akcigit, Grisby and Nicholas, therefore, can be seen as the starting point for the globalisation of the American model of capitalism.

Akcigit, Grisby and Nicholas state that during the 1880s emerged a belief that “geographic connectivity” should increase for there to be a rise in innovation: this increase would open up new markets for businesses to sell to. Here Akcigit, Grisby and Nicholas rehearse a well-recognised argument that improvements in geographic connectivity lead to an increase in globalisation, and, therefore, advancements in transport technology are also an important factor for globalisation (Rodriguez 1999).

Another aspect discussed by Akcigit, Grisby and Nicholas is the link between the amount of investment of American states on transport infrastructure and the amount of innovation emerging from said states. Here it is shown that the more a state invested on transport infrastructure the more innovations came from that state. For instance, the authors mention that in the golden era of innovation the Midwest played a big part in US innovation via manufacturing. However, due to the constant value-seeking attitude towards capitalistic globalisation the contemporary Midwest is not as prosperous as it once was (Castle 1995). However, the question as to whether these states developed in terms of overall population is unanswered. As Banister and Berechman (2001) argue, the geographic connectivity aspects of globalisation may see areas lose resources, skills and, in turn, become poorer.

In terms of what could be improved in the paper by Akcigit, Grisby and Nicholas, the first thing to note is that it only highlights the level of innovation in terms of the amount of granted patents. This is unlike works conducted by the likes of Feldman and Florida (1994) who not only seek to see the level of innovation in each state but also what particular sector the innovations were in. The paper by Feldman and Florida (1994) also provides more detail of how many of the innovations were successful in terms of whether they were the technological underpinnings for future developments in a specific sector.

Akcigit, Grisby and Nicholas suggest that all of the American states where transport and innovation increased also saw a reduction in inequality. In fact, in many cases inequality amongst the most innovative of states rose. This concurs with other research which suggests that inequality is a by-product of globalisation (Piketty and Saez, 2003).

A possible venue of research along the lines suggested by the paper is the importance of the advancement in transport technology and the role that it played in being able to create geographic connectivity. This link can be seen in the work of Usselman (2002).

Castle, E.N., (1995). The Changing American Countryside: Rural People and Places. Lawrence, KS: University Press of Kansas.

Feldman, M.P. and Florida, R., (1994). “The Geographic Sources of Innovation: Technological Infrastructure and Product Innovation in the United States.” Annals of the Association of American Geographers 84(2), pp.210-229.

Abstract: The fall of labor’s share of GDP in the United States and many other countries in recent decades is well documented but its causes remain uncertain. Existing empirical assessments of trends in labor’s share typically have relied on industry or macro data, obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and international sources and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of “superstar firms.” If globalization or technological changes advantage the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms with high profits and a low share of labor in firm value-added and sales. As the importance of superstar firms increases, the aggregate labor share will tend to fall. Our hypothesis offers several testable predictions: industry sales will increasingly concentrate in a small number of firms; industries where concentration rises most will have the largest declines in the labor share; the fall in the labor share will be driven largely by between-firm reallocation rather than (primarily) a fall in the unweighted mean labor share within firms; the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; and finally, such patterns will be observed not only in U.S. firms, but also internationally. We find support for all of these predictions.

In the last few years, inequality has been at the center of many political and academic debates. It turns out that, although less mentioned in these debates, the rapid growth of some developing countries in the last decades has actually decreased global inequality. But then, why is there a big debate about inequality? The issue is that, on the other hand, inequality in developed countries has been increasing over time. From the perspective of the functional distribution of income between labor and capital, one of the indicators of this increase in inequality is that the labor’s share of GDP has been falling in the United States and other countries in recent decades. These forces have generated winners and losers. As economist Branko Milanovic points out with his famous “elephant chart,” the middle class of the world and the very rich of the world are the two groups whose incomes have increased more rapidly. In contrast, it can be easily seen that there are large groups of people uncomfortable with increased inequality. Moreover, the factors assumed to be causing inequality have taken a vital role in political debates and recent elections.

“Elephant Chart”: Lakner & Milanovic (2016)

In this context, it is extremely important to understand what is driving these changes in inequality. There are different approaches to understand the increase in inequality in developed countries. The two main perspectives point to the importance of top incomes and changes in the tax system (e.g. Piketty and Saez, 2014), on one hand, and to changes in the labor market, mainly related to the incorporation of technological change that is more favorable to skilled workers (e.g. Autor, 2014), on the other. More recent approaches have begun to more directly incorporate the role of firms. For example, a growing literature estimates models to separate the firm’s and employee’s contributions to wage differences via double fixed-effects models, with many studies finding that firm wage effects account for approximately 20% of the overall variance of wages and have had an increasingly important role over time (e.g. Card et al., 2016). However, while we can all see that “superstar firms” like Apple, Microsoft, Google or many others in different sectors of the economy are growing very quickly, we still do not know what their effect of inequality is.

Do these “superstar firms” increase inequality because they are responsible for the decrease in labor’s share? The paper by Autor, Dorn, Katz, Patterson and Van Reenen addresses exactly this issue. If we are interested in understanding the role of firms in the increase in inequality, it is particularly important to answer the question of whether the decrease in labor’s share of income can be explained by technological changes occurring within firms, or if it is better explained by a rise of “superstar” firms, which tend to use new technologies and are more capital-intensive. The main argument of the authors is that markets have changed in such a way that firms with superior quality, lower costs, or greater innovation get disproportionately high rewards relative to previous periods. Since these “superstar firms” have higher profit levels, they also tend to have a lower share of labor in sales and value-added. Therefore, as these firms gain market share across a wide range of sectors, the aggregate share of labor falls. In this way, “superstar firms” are one of the drivers of the decrease in labor’s share (in favor of capital’s share) of value added.

Before they start developing the evidence for this argument, the authors clearly document the fall in labor’s share of GDP in the United States and other developed countries. After that, they formalize their main argument in a model of “superstar firms,” in order to derive the set of predictions that will be taken to the data. With this model in hand, the authors use several sources of information (U.S. Economic Census, KLEMS, UN Comtrade Database, and others) to run a series of regressions and decompositions to analyze the testable predictions of the model. First, the authors find that sales concentration levels have risen in most sectors. Second, they show that the larger decreases in labor’s share are observed in industries where concentration has increased the most. Third, by comparing the weighted and unweighted mean of labor’s share, the authors conclude that the fall in labor’s share has an important component of reallocation between (and not within) firms. Furthermore, they find that the between-firm reallocation of labor’s share is greatest in the sectors that are concentrating the most. Finally, these patterns are not only present in the US but also in many European countries.

Overall, all of these findings are consistent with the idea of a rise of “superstar firms” that have lower labor’s share, and which have gained more importance by concentrating large shares of sales in different sectors of the economy. It should be noted, however, that the authors do not provide a clean causal identification of the superstar firm model. The empirical exercises are done carefully and controlling for the factors that can more clearly affect the tested relationships. The use of fixed effects and trends by industry allow the authors to obtain identification exclusively from the acceleration or deceleration of labor’s shares and concentration conditional on these controlled trends. Thus, any potential threat to this identification strategy would have to come from other factors not captured by these trends or fixed effects and which are correlated with industry concentration and inequality.

This paper makes a major contribution by pointing out the role of “superstar firms” in explaining increasing inequality and opens some avenues for future research in a direction that had not been typically considered in the literature. In this sense, a particularly interesting direction would be to use the matched employer-employee databases with census data on sales to test if industry concentration has impacts on the firm component of wages and the within and between firm decomposition in each sector.

Finally, the paper addresses the question of what is the driver of the growth of these “superstar firms.” The main debate here is whether the rise of these “superstar firms” and industry concentration are associated with competitive forces, or if they are a signal of an economy with competition problems. Increased concentration can be a result of technological changes: some sectors could be introducing technologies that have a “winner takes all” aspect. An alternative, more worrisome story is that leading firms are less exposed to competition because they can create barriers to entry or have more lobbying power. The authors provide evidence that is somewhat comforting about this point. They show that concentration is greater in industries experiencing faster technical change, approximated either by patent activity or by total factor productivity growth. However, this evidence is still subject to debate. It could be the case that these originally innovative firms are now using their market power to generate barriers to entry. This can be even more important in some technology sectors where network effects generate an important advantage to the innovators. I think this discussion is actually one of the main directions where this stream of research can be expanded and complemented in the future. In this sense, for example, sector-specific partial equilibrium models could allow formalizing the product and labor markets under innovation dynamics, and such models could be estimated using data for specific industries and structural econometrics estimation techniques.

To sum up, I think that this paper makes a major contribution by pointing out the effect of “superstar firms” on the decrease of labor’s share of GDP, and therefore increased inequality in developed countries. Additionally, this paper opens several avenues for future work in order to generate more evidence consistent with the “superstar firms” model and, critically, to understand its causes and consequences at the individual micro level, especially using matched individual and firm level databases and sector-specific analysis. To understand the relationship between firms and inequality is a key task in a world of “superstar firms,” and these are key inputs for the discussion of, for example, the roles of tax policies, labor market institutions and their relationship with the increasing heterogeneity of firms.

Abstract: Exploiting a newly constructed dataset on county-level variation in Prohibition status from 1933 to 1939, this paper asks two questions: what were the effects of the repeal of federal prohibition on infant mortality? And were there any significant externalities from the individual policy choices of counties and states on their neighbors? We find that dry counties with at least one wet neighbor saw baseline infant mortality increase by roughly 3% while wet counties themselves saw baseline infant mortality increase by roughly 2%. Cumulating across the six years from 1934 to 1939, our results indicate an excess of 13,665 infant deaths that could be attributable to the repeal of federal Prohibition in 1933.

In 1919, the National Prohibition Act (also known as Volstead Act), which passed with the support of American rural protestants and social progressives, mandated that “no person shall manufacture, sell, barter, transport, import, export, deliver, furnish or possess any intoxicating liquor.” The 1920s became the decade when Al Capone operated in the Canadian and Mexican borders smuggling alcohol with the well-known subsequent boost to organized crime. President Roosevelt lifted Prohibition in 1933, although its rejection was through local referendums or elections. The repeal of Prohibition in some parts of the country divided the US into ‘dry’ and ‘wet’ areas. In dry areas, people either abstained, or were forced to buy alcohol sometimes from toxic homebrews of methanol at illegal underground bars or from ‘wet’ neighbouring counties. Meanwhile, in ‘wet’ areas, the party was on! Interestingly enough, the end of the Prohibition created what epidemiologists call ‘a natural experiment’. These experiments arise from historical events that affect some people, communities or societies, but not others. This divergence offers the possibility of learning how political choices ultimately affect people’s lives, for better or for worse.

To explore the health impacts of the repeal of the National Prohibition Act, Jacks, Pendakur and Shigeoka (2017) created a newly county-level dataset on variations in prohibition status from 1933 to 1939, and related it to previous data on infant mortality from Fishback et al. (2011) and to additional controls (such as retail sales, New Deal spending, urbanisation and so on). They addressed two questions: (1) what were the effects of the repeal of federal Prohibition on infant mortality?; and (2) were there any significant externalities from the individual policy choices of counties and states on their neighbours? In relation to the first question, they found that the effects were quite small: from 1934 until 1939, there was an excess of 13,665 infant deaths (or 1.2 additional deaths per 1,000 live births) that could be attributed to the repeal of the Prohibition in 1933. Indeed, Fishback found that the effects of the New Deal or climatic variations had greater impact on infant mortality (Fishback 2007; 2011). As for the second question, their results indicated that cross-border policy externalities were likely to be important, and that the impact of the prohibition status of individual county on infant mortality was driven by the prohibition status of its neighbours, with higher results on infant mortality for dry counties bordering with wet neighbours.

A very interesting feature of the paper is the methodological approach used in order to recognise the possibility of policy externalities across county borders. Due to spillovers and the open economy, it was not only the county’s choice (the county’s status with regards to prohibition), but, indeed, the prohibition status of its neighbours. Hence, they distinguished among counties that allow the sale of alcohol within their borders (‘wet’ counties), ‘dry’ countries with also ‘dry’ neighbours, and ‘dry’ counties next to a wet neighbours (‘dryish’ counties). In addition to several robustness tests, I particularly like the border-pair discontinuity design considering neighbouring county-pairs. This approach follows a modification of the methodology developed by Dube et al. (2010). The idea is that given the social and economic similarities between neighbouring counties, these are likely to be a good suitable control group as they share common, but unobserved county characteristics with the treatment group. In other words, in this identification strategy, the prohibition status of counties within a county-pair is uncorrelated with the differences in residual infant mortality in either county. This strategy, in turn, gets rid of the need for instrumental variables to limit biases imparted by unobserved or unmeasured confounders correlated with Prohibition.

While this is a really interesting paper, given the small effects, it is possible that the hypothesised causal mechanism between Prohibition, maternal alcohol consumption during pregnancy (from which no data exist) and infant mortality does not fully capture the effects of the Prohibition on health. If that is the case, the selection of infant mortality data is likely to be underestimating the causal effect of Prohibition on health. For example, in The Body Economic, Stuckler and Basu (2013) argued that during the Great Depression the states with the most stringent Prohibition campaigns lowered adult drinking related deaths by around 20% and also diminished suicides rates substantially. Yet, the fact that Jacks et al. (2017) have been able to find effects of the Prohibition on infant mortality highlights the relevance of the Prohibition on health and warrants further research, a research nested into the wider literature of the Great Depression and the New Deal.

Abstract: Why are international financial institutions important? This article reassesses the role of the loans issued with the support of the League of Nations. These long-term loans constituted the financial basis of the League’s strategy to restore the productive basis of countries in central and eastern Europe in the aftermath of the First World War. In this article, it is argued that the League’s loans accomplished the task for which they were conceived because they allowed countries in financial distress to access capital markets. The League adopted an innovative system of funds management and monitoring that ensured the compliance of borrowing countries with its programmes. Empirical evidence is provided to show that financial markets had a positive view of the League’s role as an external, multilateral agent, solving the credibility problem of borrowing countries and allowing them to engage in economic and institutional reforms. This success was achieved despite the League’s own lack of lending resources. It is also demonstrated that this multilateral solution performed better than the bilateral arrangements adopted by other governments in eastern Europe because of its lower borrowing and transaction costs.

Review by Vincent Bignon (Banque de France, France)

Flores and Decorzant’s paper deals with the achievements of the League of Nations in helping some central and Eastern European sovereign states to secure market access during in the Interwar years. Its success is assessed by measuring the financial performance of the loans of those countries and is compared with the performance of the loans issued by a control group made of countries of the same region that did not received the League’s support. The comparison of the yield at issue and fees paid to issuing banks allows the authors to conclude that the League of Nations did a very good job in helping those countries, hence the suggestion in the title to go multilateral.

The authors argue that the loans sponsored by the League of Nation – League’s loan thereafter – solved a commitment issue for borrowing governments, which consisted in the non-credibility when trying to signal their willingness to repay. The authors mention that the League brought financial expertise related to the planning of the loan issuance and in the negotiations of the clauses of contracts, suggesting that those countries lacked the human capital in their Treasuries and central banks. They also describe that the League support went with a monitoring of the stabilization program by a special League envoy.

Empirical results show that League loans led to a reduction of countries’ risk premium, thus allowing relaxing the borrowing constraint, and sometimes reduced quantity rationing for countries that were unable to issue directly through prestigious private bankers. Yet the interests rates of League loans were much higher than those of comparable US bond of the same rating, suggesting that the League did not create a free lunch.

Besides those important points, the paper is important by dealing with a major post war macro financial management issue: the organization of sovereign loans issuance to failed states since their technical administrative apparatus were too impoverished by the war to be able to provide basic peacetime functions such as a stable exchange rate, a fiscal policy with able tax collection. Comparison is made of the League’s loans with those of the IMF, but the situation also echoes the unilateral post WW 2 US Marshall plan. The paper does not study whether the League succeeded in channeling some other private funds to those countries on top of the proceeds of the League loans and does not study how the funds were used to stabilize the situation.

The paper belongs to the recent economic history tradition that aims at deciphering the explanations for sovereign debt repayment away from the gunboat diplomacy explanation, to which Juan Flores had previously contributed together with Marc Flandreau. It is also inspired by the issue of institutional fixes used to signal and enforce credible commitment, suggesting that multilateral foreign fixes solved this problem. This detailed study of financial conditions of League loans adds stimulating knowledge to our knowledge of post WW1 stabilization plans, adding on Sargent (1984) and Santaella (1993). It’s also a very nice complement to the couple of papers on multilateral lending to sovereign states by Tunker and Esteves (2016a, 2016b) that deal with 19th century style multilateralism, when the main European powers guaranteed loans to help a few states secured market access, but without any founding of an international organization.

But the main contribution of the paper, somewhat clouded by the comparison with the IMF, is to lead to a questioning of the functions fulfilled by the League of Nations in the Interwar political system. This bigger issue surfaced at two critical moments. First in the choice of the control group that focus on the sole Central and Eastern European countries, but does not include Germany and France despite that they both received external funding to stabilize their financial situation at the exact moment of the League’s loans. This brings a second issue, one of self-selection of countries into the League’s loans program. Indeed, Germany and France chose to not participate to the League’s scheme despite the fact that they both needed a similar type of funding to stabilize their macro situation. The fact that they did not apply for financial assistance means either that they have the qualified staff and the state apparatus to signal their commitment to repay, or that the League’s loan came with too harsh a monitoring and external constraint on financial policy. It is as if the conditions attached with League’ loans self-selected the good-enough failed states (new states created out of the demise of the Austro-Hungarian Empire) but discouraged more powerful states to apply to the League’ assistance.

Now if one reminds that the promise of the League of Nations was the preservation of peace, the success of the League loans issuance was meager compared to the failure in preserving Europe from a second major war. This of course echoes the previous research of Juan Flores with Marc Flandreau on the role of financial market microstructure in keeping the world in peace during the 19th century. By comparison, the League of Nations failed. Yet a successful League, which would have emulated Rothschild’s 19th century role in peace-keeping would have designed a scheme in which all states in need -France and Germany included – would have borrowed through it.

This leads to wonder the function assigned by their political brokers to the program of financial assistance of the League. As the IMF, the League was only able to design a scheme attractive to the sole countries that had no allies ready or strong-enough to help them secure market access. Also why did the UK and the US chose to channel funds through the League rather than directly? Clearly they needed the League as a delegated agent. Does that means that the League was another form of money doctors or that it acts as a coalition of powerful countries made of those too weak to lend and those rich but without enforcement power? This interpretation is consistent with the authors’ view “the League (…) provided arbitration functions in case of disputes.”

In sum the paper opens new connections with the political science literature on important historical issues dealing with the design of international organization able to provide public goods such as peace and not just helping the (strategic) failed states.

Can a bank run be stopped? Government guarantees and the run on Continental Illinois

Mark A Carlson (Bank for International Settlements) and Jonathan Rose (Board of Governors of the Federal Reserve)

Abstract: This paper analyzes the run on Continental Illinois in 1984. We find that the run slowed but did not stop following an extraordinary government intervention, which included the guarantee of all liabilities of the bank and a commitment to provide ongoing liquidity support. Continental’s outflows were driven by a broad set of US and foreign financial institutions. These were large, sophisticated creditors with holdings far in excess of the insurance limit. During the initial run, creditors with relatively liquid balance sheets nevertheless withdrew more than other creditors, likely reflecting low tolerance to hold illiquid assets. In addition, smaller and more distant creditors were more likely to withdraw. In the second and more drawn out phase of the run, institutions with relative large exposures to Continental were more likely to withdraw, reflecting a general unwillingness to have an outsized exposure to a troubled institution even in the absence of credit risk. Finally, we show that the concentration of holdings of Continental’s liabilities was a key dynamic in the run and was importantly linked to Continental’s systemic importance.

Review by Anthony Gandy (ifs University College)

I have to thank Bernardo Batiz-Lazo for spotting this paper and circulating it through NEP-HIS, my interest in this is less research focused than teaching focused. Having the honour of teaching bankers about banking, sometimes I am asked questions which I find difficult to answer. One such question has been ‘why are inter-bank flows seen as less volatile, than consumer deposits?’ In this very accessible paper, Carlson and Rose answers this question by analysing the reality of a bank run, looking at the raw data from the treasury department of a bank which did indeed suffer a bank run: Continental Illinois – which became the biggest banking failure in US history when it flopped in 1984.

For the business historian, the paper may lack a little character as it rather skimps over the cause of Continental’s demise, though this has been covered by many others, including the Federal Deposit Insurance Corporation (1997). The paper briefly explains the problems Continental faced in building a large portfolio of assets in both the oil and gas sector and developing nations in Latin America. A key factor in the failure of Continental in 1984, was the 1982 failure of the small bank Penn Square Bank of Oklahoma. Cushing, Oklahoma is the, quite literally, hub (and one time bottleneck) of the US oil and gas sector. The the massive storage facility in that location became the settlement point for the pricing of West Texas Intermediate (WTI), also known as Texas light sweet, oil. Penn Square focused on the oil sector and sold assets to Continental, according the FDIC (1997) to the tune of $1bn. Confidence in Continental was further eroded by the default of Mexico in 1982 thus undermining the perceived quality of its emerging market assets.

Depositors queuing outside the insolvent Penn Square Bank (1982)

In 1984 the failure of Penn would translate into the failure of the 7th largest bank in the US, Continental Illinois. This was a great illustration of contagion, but contagion which was contained by the central authorities and, earlier, a panel of supporting banks. Many popular articles on Continental do an excellent job of explaining why its assets deteriorated and then vaguely discuss the concept of contagion. The real value of the paper by Carlson and Rose comes from their analysis of the liability side of the balance sheet (sections 3 to 6 in the paper). Carlson and Rose take great care in detailing the make up of those liabilities and the behaviour of different groups of liability holders. For instance, initially during the crisis 16 banks announced a advancing $4.5bn in short term credit. But as the crisis went forward the regulators (Federal Deposit Insurance Corporation, the Federal Reserve and the Office of the Comptroller of the Currency) were required to step in to provide a wide ranging guarantee. This was essential as the bank had few small depositors who, in turn, could rely on the then $100,000 depositor guarantee scheme.

It would be very easy to pause and take in the implications of table 1 in the paper. It shows that on the 31st March 1984, Continental had a most remarkable liability structure. With $10.0bn of domestic deposits, it funded most of its books through $18.5bn of foreign deposits, together with smaller amounts of other wholesale funding. However, the research conducted by Carlson and Rose showed that the intolerance of international lenders, did become a factor but it was only one of a number of effects. In section 6 of the paper they look at the impact of funding concentration. The largest ten depositors funded Continental to the tune of $3.4bn and the largest 25 to $6bn dollars, or 16% of deposits. Half of these were foreign banks and the rest split between domestic banks, money market funds and foreign governments.

Initially, `run off’, from the largest creditors was an important challenge. But this was related to liquidity preference. Those institutions which needed to retain a highly liquid position were quick to move their deposits out of Continental. One could only speculate that these withdrawals would probably have been made by money market funds. Only later, in a more protracted run off, which took place even after interventions, does the size of the exposure and distance play a disproportionate role. What is clear is the unwillingness of distant banks to retain exposure to a failing institution. After the initial banking sector intervention and then the US central authority intervention, foreign deposits rapidly decline.

It’s a detailed study, one which can be used to illustrate to students both issues of liquidity preference and the rationale for the structures of the new prudential liquidity ratios, especially the Net Stable Funding Ratio. It can also be used to illustrate the problems of concentration risk – but I would enliven the discussion with the addition of the more colourful experience of Penn Square Bank- a banks famed for drinking beer out of cowboy boots!

We identify America’s First Great Moderation, a recession-free 16-year period from 1841 until 1856, that represents the longest economic expansion in U.S. history. Occurring in the wake of the debt-deleveraging cycle of the late 1830s, this “take-off” period’s high rates of economic growth and relatively-low volatility enabled the U.S. economy to escape downturns despite the absence of a central bank. Using new high frequency data on industrial production, we show that America’s First Great Moderation was primarily driven by a boom in transportation-goods investment, attributable to both the wider adoption of steam railroads and river boats and the high expected returns for massive wooden clipper ships following the discovery of gold in California. We do not find evidence that agriculture (i.e., cotton), domestic textile production, or British economic conditions played any significant role in this moderation. The First Great Moderation ended with a sharp decline in transportation investment and bank credit during the downturn of 1857-8 and the coming American Civil War. Our empirical analyses indicate that the low-volatility states derived for both annual industrial production and monthly stock prices during the First Great Moderation are similar to those estimated for the Second Great Moderation (1984-2007).

Review by Natacha Postel-Vinay (University of Warwick)

Those who like to study the causes of business fluctuations are often primarily interested in severe downturns, or sometimes wild upswings. They may be tempted to gloss over periods of relative calm where not much seems to be happening. Yet there is a good case for studying such phenomena: surely a long period of low volatility in output, prices and unemployment combined with relatively high sustained growth would make many policy makers happy. As such they deserve our attention.

The Great Moderation is usually thought of as one such period when, from the 1980s up to 2007, US economic growth became both more sustained and much less volatile. The causes of the Great Moderation are still being debated, and range from better monetary policy to major structural changes such as the development of information technologies to sheer luck (for example, an absence of oil shocks). Less well-known is the fact that the US economy experienced a similar phenomenon more than a century earlier, from the 1840s to the mid-1850s. In their paper, Davis and Weidenmier draw our attention to this period as it was, in their view, America’s First Great Moderation. While much of the paper is spent demonstrating just that, they also look for its causes, and argue that important structural changes in the transportation industry were probably at the origin of this happy experience.

Despite being sometimes pointed out as America’s “take-off” period (Rostow, 1971), the idea that this was the US’s First Great Moderation is far from straightforward. This is partly because the period has been commonly known for its relative financial instability, with for instance financial panics in the late 1930s, 1940s and 1950s. In addition, the National Bureau of Economic Research (NBER)’s official business cycle data do not go further back than 1854, which itself results from the fact that most of the extant data on pre-1854 output is qualitative. Thorp’s Business Annals (1926), for example, are primarily based on anecdotal newspaper reports. Thorp identifies a recession in almost every other year, which Davis and Weidenmier think is a gross overestimation.

Instead, the authors use Davis’s (2004) index of industrial production (IP) and defend their choice by pointing out a number of things. First, this is a newer, high-frequency series which despite its industrial focus is much more precise than, for example, Gallman’s trend GDP data. It is based on 43 annual components in the manufacturing and mining industries which were consistently derived from 1790 to World War I. The series does not contain any explicit information on the agricultural sector, which produced more than half of US output in the antebellum era. However, Davis and Weidenmier argue that any large business fluctuations apparent in this sector would also be reflected in the IP index as the demand for industrial goods was very much tied to farm output. Conversely, the demand for say, lumber, could be intimately related to business conditions in the construction and railroad industries.

Simply looking at standard deviations makes clear that the 1841-1856 period was indeed one of especially low volatility and sustained growth in industrial production, with no absolute normal declines in output. From this data it is thus apparent that even the well-known 1837 financial panic was not followed by any protracted recession, thereby confirming Temin’s (1969) earlier suspicion. Testing more rigorously for breaks in the series, their Markov regime-switching model suggests that the probability of a low-volatility state indeed rises the most during this period as compared to the early and late 19th-century periods. Applying the same model up to the recent era, it even appears that the two Great Moderations were similar in magnitude – a remarkable result.

But what could explain this apparently unique phenomenon? To answer this question, Davis and Weidenmier first decompose industrial production into several sectors such as metal products, transportation machinery, lumber, food, textiles, printing, chemicals and leather. They then find that the probability of faster growth and lower volatility during the First Great Moderation is significantly higher for the transportation-goods industry. This corresponds to the general idea that the “transportation revolution” (especially in railroads and ships) was an important aspect of America’s take-off. However, increased production in transportation goods could be a result of increased demand in the economy as a whole. The authors then refute this possibility by showing that transportation production preceded all other industrial sector increases in this period, which would tend to confirm the importance of transportation investment spillover effects into other sectors.

Davis and Weidenmier therefore make a convincing case that the Great Moderation should in fact be called the Second Great Moderation, since a first one is clearly apparent from the 1840s to the mid-1850s. Interestingly, they emphasize that in both cases deep structural changes in the economy seem to have been at work, especially in the realm of general purpose technologies, with significant spillovers (transportation in one case, IT in the other).

An important question left to answer is the extent to which an era of the “Great Moderation” type is to be desired, and on what grounds. Although aiming at a quiet yet prosperous era seems legitimate, it is important to remind ourselves that the 1850s ended with a severe financial and economic crisis which some argue had its roots in financial speculation and overindebtedness in preceding years. Likewise, we all know how the 2000s sadly ended. The “Second” Great Moderation also saw significant increases in inequality. Davis and Weidenmier acknowledge not being able to account for financial and banking developments during this era; perhaps this needs to be investigated further (or at least pondered upon). One may ask, indeed, whether such periods of prosperity may not bear in themselves the seeds of their own demise.

Gallman, Robert. (1966). “Gross National Product in the United States, 1834-1909” in Dorothy S. Brady (ed.) Output, Employment, and Productivity in the United States after 1800. New York, Columbia University Press.